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Addressing Knowledge Gaps in the 2013 ACC/AHA Guideline on the Assessment of Cardiovascular Risk: a Review of Recent Coronary Artery Calcium Literature

  • Coronary Heart Disease (S. Virani and S. Naderi, Section Editors)
  • Published:
Current Atherosclerosis Reports Aims and scope Submit manuscript

Abstract

Purpose of Review

Coronary artery calcium (CAC) has been proposed as an integrator of information from traditionally measured, non-traditionally measured, and unmeasured risk factors for coronary atherosclerosis. The 2013 American College of Cardiology/American Heart Association Guideline on the Assessment of Cardiovascular Risk identified several knowledge gaps regarding CAC, including radiation risks, cost-effectiveness, and improving discrimination and reclassification of estimated risk over the Pooled Cohort Equations in the ACC/AHA Atherosclerotic Cardiovascular Disease Estimator. In this review, we focus on recent CAC literature addressing these knowledge gaps. We further highlight the potential for CAC to enrich future randomized controlled trials.

Recent Findings

The use of CAC allows for personalization of cardiovascular risk despite the presence or absence of traditional risk factors across many demographics. Avenues to reduce radiation exposure associated with CAC scanning include increasing the interval between scans for those with CAC scores of zero and estimating CAC from non-cardiac gated CT scans. While limited studies have suggested cost-effectiveness in cardiac risk assessment with the incorporation of CAC in screening algorithms, several studies have demonstrated the ability of CAC to identify non-traditional risk factors that may be used to expand cardiovascular risk personalization in other high-risk populations.

Summary

Literature from the past 2 years further supports CAC as a strong marker to personalize cardiac risk assessment. While multiple potential avenues to reduce radiation are available and cost-effectiveness analyses are encouraging, further studies are necessary to clarify patient selection for CAC scanning given the interplay between CAC and other imaging modalities in risk personalization algorithms.

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Abbreviations

CAC:

Coronary artery calcium

ACC:

American College of Cardiology

AHA:

American Heart Association

ASCVD:

Atherosclerotic cardiovascular disease

CCTA:

Coronary computed tomography angiography

CVD:

Cardiovascular disease

MESA:

Multi-ethnic Study of Atherosclerosis

CRP:

C-reactive protein

MPI:

Myocardial perfusion imaging

ABI:

Ankle-brachial index

PCSK9:

Proprotein convertase subtilisin/kexin type 9

SPECT:

Single photon emission computed tomography

HR:

Hazard ratio

OR:

Odds ratio

RR:

Relative risk

DLR:

Diagnostic likelihood ratio

AUC:

Area under the curve

ROS:

Receiver operating statistics

EFV:

Epicardial fat volume

COPD:

Chronic obstructive pulmonary disease

ED:

Erectile dysfunction

NAFLD:

Non-alcoholic fatty liver disease

SLE:

Systemic lupus erythematous

References

Papers of particular interest, published recently, have been highlighted as: • Of importance •• Of major importance

  1. Roger VL, Go AS, Lloyd-Jones DM, et al. Heart disease and stroke statistics–2011 update: a report from the American Heart Association. Circulation. 2011;123(4):e18–209. doi:10.1161/CIR.0b013e3182009701.

    Article  PubMed  Google Scholar 

  2. Heidenreich PA, Trogdon JG, Khavjou OA, et al. Forecasting the future of cardiovascular disease in the United States: a policy statement from the American Heart Association. Circulation. 2011;123(8):933–44. doi:10.1161/CIR.0b013e31820a55f5.

    Article  PubMed  Google Scholar 

  3. Gaziano T, Reddy KS, Paccaud F, et al. Cardiovascular disease. The international bank for reconstruction and development/The World Bank. 2006.

  4. Goff DC, Lloyd-Jones DM, Bennett G, et al. 2013 ACC/AHA guideline on the assessment of cardiovascular risk: a report of the American College of Cardiology/American Heart Association task force on practice guidelines. J Am Coll Cardiol. 2014; 63(25_PA). doi:10.1016/j.jacc.2013.11.005.

  5. Cho YK, Jung CH, Kang YM, et al. 2013 ACC/AHA cholesterol guideline versus 2004 NCEP ATP III guideline in the prediction of coronary artery calcification progression in a Korean population. J Am Heart Assoc. 2016;5, e003410. doi:10.1161/JAHA.116.003410.

    Article  PubMed  PubMed Central  Google Scholar 

  6. Muntner P, Colantonio LD, Cushman M, et al. Validation of the atherosclerotic cardiovascular disease pooled cohort risk equations. JAMA. 2014;311(14):1406–15. doi:10.1001/jama.2014.2630.

    Article  PubMed  PubMed Central  Google Scholar 

  7. Ridker PM, Cook NR. Statins: new American guidelines for prevention of cardiovascular disease. Lancet. 2013;382(9907):1762–5. doi:10.1016/S0140-6736(13)62388-0.

    Article  PubMed  Google Scholar 

  8. Blaha MJ, Silverman MG, Budoff MJ. Is there a role for coronary artery calcium scoring for management of asymptomatic patients at risk for coronary artery disease?: clinical risk scores are not sufficient to define primary prevention treatment strategies among asymptomatic patients. Circ Cardiovasc Imaging. 2014;7(2):398–408. doi:10.1161/CIRCIMAGING.113.000341. discussion 408.

    Article  PubMed  Google Scholar 

  9. Kianoush S, Al Rifai M, Cainzos-Achirica M, et al. An update on the utility of coronary artery calcium scoring for coronary heart disease and cardiovascular disease risk prediction. Curr Atheroscler Rep. 2016;18(3):13. doi:10.1007/s11883-016-0565-6.

    Article  PubMed  Google Scholar 

  10. Robbins JM, Petrone AB, Carr JJ, et al. Association of ideal cardiovascular health and calcified atherosclerotic plaque in the coronary arteries: the National Heart, Lung, and Blood Institute Family Heart Study. Am Heart J. 2015;169(3):371–378.e1. doi:10.1016/j.ahj.2014.12.017.

    Article  PubMed  PubMed Central  Google Scholar 

  11. Saleem Y, DeFina LF, Radford NB, et al. Association of a favorable cardiovascular health profile with the presence of coronary artery calcification. Circ Cardiovasc Imaging. 2014;8(1):pii:e001851. doi:10.1161/CIRCIMAGING.114.001851.

    Article  Google Scholar 

  12. Bensenor IM, Goulart AC, Santos IS, et al. Association between a healthy cardiovascular risk factor profile and coronary artery calcium score: results from the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil). Am Heart J. 2016;174:51–9. doi:10.1016/j.ahj.2015.12.018.

    Article  PubMed  Google Scholar 

  13. Joshi PH, Patel B, Blaha MJ, et al. Coronary artery calcium predicts cardiovascular events in participants with a low lifetime risk of cardiovascular disease: the Multi-Ethnic Study of Atherosclerosis (MESA). Atherosclerosis. 2016;246:367–73. doi:10.1016/j.atherosclerosis.2016.01.017. In patients with no traditional cardiovascular risk factors, CAC helps further personalize risk assessment.

    Article  CAS  PubMed  Google Scholar 

  14. Nasir K, Bittencourt MS, Blaha MJ, et al. Implications of coronary artery calcium testing among statin candidates according to American College of Cardiology/American Heart Association cholesterol management guidelines: MESA (Multi-Ethnic Study of Atherosclerosis). J Am Coll Cardiol. 2015;66(15):1657–68. doi:10.1016/j.jacc.2015.07.066. CAC helps further personalize cardiovascular risk assessment across all strata of ASCVD risk estimation.

    Article  CAS  PubMed  Google Scholar 

  15. Yeboah J, Young R, McClelland RL, et al. Utility of nontraditional risk markers in atherosclerotic cardiovascular disease risk assessment. J Am Coll Cardiol. 2016;67(2):139–47. doi:10.1016/j.jacc.2015.10.058.

    Article  PubMed  PubMed Central  Google Scholar 

  16. McClelland RL, Jorgensen NW, Budoff M, et al. 10-year coronary heart disease risk prediction using coronary artery calcium and traditional risk factors: derivation in the MESA (Multi-Ethnic Study of Atherosclerosis) with validation in the HNR (Heinz Nixdorf Recall) study and the DHS (Dallas Heart Study). J Am Coll Cardiol. 2015;66(15):1643–53. doi:10.1016/j.jacc.2015.08.035.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Messenger B, Li D, Nasir K, et al. Coronary calcium scans and radiation exposure in the multi-ethnic study of atherosclerosis. Int J Cardiovasc Imaging. 2016;32(3):525–9. doi:10.1007/s10554-015-0799-3.

    Article  PubMed  Google Scholar 

  18. Alluri K, McEvoy JW, Dardari ZA, et al. Distribution and burden of newly detected coronary artery calcium: results from the Multi-Ethnic Study of Atherosclerosis. J Cardiovasc Comput Tomogr. 2015;9(4):337–344.e1. doi:10.1016/j.jcct.2015.03.015.

    Article  PubMed  PubMed Central  Google Scholar 

  19. Valenti V, O Hartaigh B, Heo R, et al. A 15-year warranty period for asymptomatic individuals without coronary artery calcium: a prospective follow-up of 9,715 individuals. JACC Cardiovasc Imaging. 2015;8(8):900–9. doi:10.1016/j.jcmg.2015.01.025. Suggests that patients mwith zero CAC may have a “warranty” of 15-years before repeat CAC scan.

    Article  PubMed  PubMed Central  Google Scholar 

  20. Ahmed W, de Graaf MA, Broersen A, et al. Automatic detection and quantification of the Agatston coronary artery calcium score on contrast computed tomography angiography. Int J Cardiovasc Imaging. 2015;31(1):151–61. doi:10.1007/s10554-014-0519-4.

    Article  PubMed  Google Scholar 

  21. Schuhbaeck A, Otaki Y, Achenbach S, et al. Coronary calcium scoring from contrast coronary CT angiography using a semiautomated standardized method. J Cardiovasc Comput Tomogr. 2015;9(5):446–53. doi:10.1016/j.jcct.2015.06.001.

    Article  PubMed  Google Scholar 

  22. Pavitt CW, Harron K, Lindsay AC, et al. Technical feasibility and validation of a coronary artery calcium scoring system using CT coronary angiography images. Eur Radiol. 2016;26(5):1493–502. doi:10.1007/s00330-015-3940-8.

    Article  PubMed  Google Scholar 

  23. Hughes-Austin JM, Dominguez 3rd A, Allison MA, et al. Relationship of coronary calcium on standard chest CT scans with mortality. JACC Cardiovasc Imaging. 2016;9(2):152–9. doi:10.1016/j.jcmg.2015.06.030.

    Article  PubMed  PubMed Central  Google Scholar 

  24. Takx RA, Isgum I, Willemink MJ, et al. Quantification of coronary artery calcium in nongated CT to predict cardiovascular events in male lung cancer screening participants: results of the NELSON study. J Cardiovasc Comput Tomogr. 2015;9(1):50–7. doi:10.1016/j.jcct.2014.11.006.

    Article  PubMed  Google Scholar 

  25. Engbers EM, Timmer JR, Mouden M, et al. Visual estimation of coronary calcium on computed tomography for attenuation correction. J Cardiovasc Comput Tomogr. 2016;10(4):327–9. doi:10.1016/j.jcct.2016.04.002.

    Article  CAS  PubMed  Google Scholar 

  26. Hecht HS, de Siqueira ME, Cham M, et al. Low-vs. standard-dose coronary artery calcium scanning. Eur Heart J Cardiovasc Imaging. 2015;16(4):358–63. doi:10.1093/ehjci/jeu218.

    Article  PubMed  Google Scholar 

  27. Willemink MJ, den Harder AM, Foppen W, et al. Finding the optimal dose reduction and iterative reconstruction level for coronary calcium scoring. J Cardiovasc Comput Tomogr. 2016;10(1):69–75. doi:10.1016/j.jcct.2015.08.004.

    Article  PubMed  Google Scholar 

  28. Takahashi M, Kimura F, Umezawa T, et al. Comparison of adaptive statistical iterative and filtered back projection reconstruction techniques in quantifying coronary calcium. J Cardiovasc Comput Tomogr. 2016;10(1):61–8. doi:10.1016/j.jcct.2015.07.012.

    Article  PubMed  Google Scholar 

  29. Cho I, Chang HJ, O Hartaigh B, et al. Incremental prognostic utility of coronary CT angiography for asymptomatic patients based upon extent and severity of coronary artery calcium: results from the COronary CT Angiography EvaluatioN For Clinical Outcomes International Multicenter (CONFIRM) study. Eur Heart J. 2015;36(8):501–8. doi:10.1093/eurheartj/ehu358.

    Article  PubMed  Google Scholar 

  30. Dedic A, Ten Kate GJ, Roos CJ, et al. Prognostic value of coronary computed tomography imaging in patients at high risk without symptoms of coronary artery disease. Am J Cardiol. 2016;117(5):768–74. doi:10.1016/j.amjcard.2015.11.058.

    Article  PubMed  Google Scholar 

  31. Durhan G, Hazirolan T, Sunman H, et al. Does coronary calcium scoring with a SCORE better predict significant coronary artery stenosis than without? Correlation with computed tomography coronary angiography. Eur Radiol. 2015;25(3):776–84. doi:10.1007/s00330-014-3477-2.

    Article  PubMed  Google Scholar 

  32. Engbers EM, Timmer JR, Ottervanger JP, et al. Prognostic value of coronary artery calcium scoring in addition to single-photon emission computed tomographic myocardial perfusion imaging in symptomatic patients. Circ Cardiovasc Imaging. 2016;9(5):pii:e003966. doi:10.1161/CIRCIMAGING.115.003966.

    Article  Google Scholar 

  33. Mahabadi AA, Lehmann N, Möhlenkamp S, et al. Noncoronary measures enhance the predictive value of cardiac CT above traditional risk factors and CAC score in the general population. JACC Cardiovasc Imaging. 2016;9(10):1177–85. doi:10.1016/j.jcmg.2015.12.024. Non-coronary values such as EFV, LA index, and TAC may suggest underlying atherosclerosis and can personalize risk assessment by identifying which patients may benefit from CAC scans.

    Article  PubMed  Google Scholar 

  34. Brodov Y, Gransar H, Rozanski A, et al. Extensive thoracic aortic calcification is an independent predictor of development of coronary artery calcium among individuals with coronary artery calcium score of zero. Atherosclerosis. 2015;238(1):4–8. doi:10.1016/j.atherosclerosis.2014.10.100.

    Article  CAS  PubMed  Google Scholar 

  35. Hu X, Frellesen C, Kerl JM, et al. Association of aortic root calcification severity with the extent of coronary artery calcification assessed by calcium-scoring dual-source computed tomography. Eur J Radiol. 2015;84(10):1910–4. doi:10.1016/j.ejrad.2015.06.003.

    Article  PubMed  Google Scholar 

  36. Tanami Y, Jinzaki M, Kishi S, et al. Lack of association between epicardial fat volume and extent of coronary artery calcification, severity of coronary artery disease, or presence of myocardial perfusion abnormalities in a diverse, symptomatic patient population: results from the CORE320 multicenter study. Circ Cardiovasc Imaging. 2015;8(3), e002676. doi:10.1161/CIRCIMAGING.114.002676.

    Article  PubMed  PubMed Central  Google Scholar 

  37. Possner M, Liga R, Gaisl T, et al. Quantification of epicardial and intrathoracic fat volume does not provide an added prognostic value as an adjunct to coronary artery calcium score and myocardial perfusion single-photon emission computed tomography. Eur Heart J Cardiovasc Imaging. 2016;17(8):885–91. doi:10.1093/ehjci/jev209.

    Article  PubMed  Google Scholar 

  38. Min JK, Lin FY, Gidseg DS, et al. Determinants of coronary calcium conversion among patients with a normal coronary calcium scan: what is the “warranty period” for remaining normal? J Am Coll Cardiol. 2010;55(11):1110–7. doi:10.1016/j.jacc.2009.08.088.

    Article  PubMed  Google Scholar 

  39. Szilveszter B, Elzomor H, Karolyi M, et al. The effect of iterative model reconstruction on coronary artery calcium quantification. Int J Cardiovasc Imaging. 2016;32(1):153–60. doi:10.1007/s10554-015-0740-9.

    Article  PubMed  Google Scholar 

  40. Chaikriangkrai K, Velankar P, Schutt R, et al. Additive prognostic value of coronary artery calcium score over coronary computed tomographic angiography stenosis assessment in symptomatic patients without known coronary artery disease. Am J Cardiol. 2015;115(6):738–44. doi:10.1016/j.amjcard.2014.12.032.

    Article  PubMed  Google Scholar 

  41. Hadamitzky M, Achenbach S, Al-Mallah M, et al. Optimized prognostic score for coronary computed tomographic angiography. J Am Coll Cardiol. 2013;62(5):468–76. doi:10.1016/j.jacc.2013.04.064.

    Article  PubMed  Google Scholar 

  42. Bavishi C, Argulian E, Chatterjee S, Rozanski A. CACS and the frequency of stress-induced myocardial ischemia during MPI: a meta-analysis. JACC Cardiovasc Imaging. 2016;9(5):580–9. doi:10.1016/j.jcmg.2015.11.023.

    Article  PubMed  Google Scholar 

  43. Barros MV, Nunes Mdo C, Braga G, et al. Role of coronary artery calcium score for risk stratification in patients with non significant perfusion defects by myocardial perfusion single photon emission computed tomography. Cardiol J. 2015;22(3):330–5. doi:10.5603/CJ.a2014.0084.

    Article  PubMed  Google Scholar 

  44. Chang SM, Nabi F, Xu J, et al. Value of CACS compared with ETT and myocardial perfusion imaging for predicting long-term cardiac outcome in asymptomatic and symptomatic patients at low risk for coronary disease: clinical implications in a multimodality imaging world. JACC Cardiovasc Imaging. 2015;8(2):134–44. doi:10.1016/j.jcmg.2014.11.008.

    Article  PubMed  Google Scholar 

  45. Hell MM, Ding X, Rubeaux M, et al. Epicardial adipose tissue volume but not density is an independent predictor for myocardial ischemia. J Cardiovasc Comput Tomogr. 2016;10(2):141–9. doi:10.1016/j.jcct.2016.01.009.

    Article  PubMed  Google Scholar 

  46. Kitagawa T, Yamamoto H, Sentani K, et al. The relationship between inflammation and neoangiogenesis of epicardial adipose tissue and coronary atherosclerosis based on computed tomography analysis. Atherosclerosis. 2015;243(1):293–9. doi:10.1016/j.atherosclerosis.2015.09.013.

    Article  CAS  PubMed  Google Scholar 

  47. Lee BC, Lee WJ, Lo SC, et al. The ratio of epicardial to body fat improves the prediction of coronary artery disease beyond calcium and Framingham risk scores. Int J Cardiovasc Imaging. 2016;32 Suppl 1:117–27. doi:10.1007/s10554-016-0912-2.

    Article  PubMed  Google Scholar 

  48. Lu MT, Park J, Ghemigian K, et al. Epicardial and paracardial adipose tissue volume and attenuation—association with high-risk coronary plaque on computed tomographic angiography in the ROMICAT II trial. Atherosclerosis. 2016;251:47–54. doi:10.1016/j.atherosclerosis.2016.05.033.

    Article  CAS  PubMed  Google Scholar 

  49. Roberts ET, Horne A, Martin SS, et al. Cost-effectiveness of coronary artery calcium testing for coronary heart and cardiovascular disease risk prediction to guide statin allocation: the Multi-Ethnic Study of Atherosclerosis (MESA). PLoS One. 2015;10(3), e0116377. doi:10.1371/journal.pone.0116377. In a modeling study, the incorporation of CAC and selectively treating patients with positive values proved to be the most cost-effective strategy.

    Article  PubMed  PubMed Central  Google Scholar 

  50. Demir OM, Bashir A, Marshall K, et al. Comparison of clinical efficacy and cost of a cardiac imaging strategy versus a traditional exercise test strategy for the investigation of patients with suspected stable coronary artery disease. Am J Cardiol. 2015;115(12):1631–5. doi:10.1016/j.amjcard.2015.03.005.

    Article  PubMed  Google Scholar 

  51. Lubbers M, Dedic A, Coenen A, et al. Calcium imaging and selective computed tomography angiography in comparison to functional testing for suspected coronary artery disease: the multicentre, randomized CRESCENT trial. Eur Heart J. 2016;37(15):1232–43. doi:10.1093/eurheartj/ehv700.

    Article  PubMed  Google Scholar 

  52. Handy CE, Desai CS, Dardari ZA, et al. The association of coronary artery calcium with noncardiovascular disease: the Multi-Ethnic Study of Atherosclerosis. JACC Cardiovasc Imaging. 2016;9(5):568–76. doi:10.1016/j.jcmg.2015.09.020.

    Article  PubMed  Google Scholar 

  53. Santos IS, Bittencourt MS, Rocco PT, et al. Relation of anxiety and depressive symptoms to coronary artery calcium (from the ELSA-Brasil baseline data). Am J Cardiol. 2016;118(2):183–7. doi:10.1016/j.amjcard.2016.04.048.

    Article  CAS  PubMed  Google Scholar 

  54. Janssen I, Powell LH, Matthews KA, et al. Relation of persistent depressive symptoms to coronary artery calcification in women aged 46 to 59 years. Am J Cardiol. 2016;117(12):1884–9. doi:10.1016/j.amjcard.2016.03.035.

    Article  PubMed  Google Scholar 

  55. Kuller LH, Lopez OL, Mackey RH, et al. Subclinical cardiovascular disease and death, dementia, and coronary heart disease in patients 80+ years. J Am Coll Cardiol. 2016;67(9):1013–22. doi:10.1016/j.jacc.2015.12.034.

    Article  PubMed  Google Scholar 

  56. Kaufman JD, Adar SD, Barr RG, et al. Association between air pollution and coronary artery calcification within six metropolitan areas in the USA (the Multi-Ethnic Study of Atherosclerosis and air pollution): a longitudinal cohort study. Lancet. 2016;388(10045):696–704. doi:10.1016/S0140-6736(16)00378-0.

    Article  CAS  PubMed  Google Scholar 

  57. Dorans KS, Wilker EH, Li W, et al. Residential proximity to major roads, exposure to fine particulate matter, and coronary artery calcium: the Framingham Heart Study. Arterioscler Thromb Vasc Biol. 2016;36(8):1679–85. doi:10.1161/ATVBAHA.116.307141.

    Article  CAS  PubMed  Google Scholar 

  58. Juonala M, Pulkki-Raback L, Elovainio M, et al. Childhood psychosocial factors and coronary artery calcification in adulthood: the Cardiovascular Risk in Young Finns Study. JAMA Pediatr. 2016;170(5):466–72. doi:10.1001/jamapediatrics.2015.4121.

    Article  PubMed  Google Scholar 

  59. Wing JJ, August E, Adar SD, et al. Change in neighborhood characteristics and change in coronary artery calcium: a longitudinal investigation in the MESA (Multi-Ethnic Study of Atherosclerosis) cohort. Circulation. 2016;134(7):504–13. doi:10.1161/CIRCULATIONAHA.115.020534.

    Article  CAS  PubMed  Google Scholar 

  60. Hjuler KF, Bottcher M, Vestergaard C, et al. Increased prevalence of coronary artery disease in severe psoriasis and severe atopic dermatitis. Am J Med. 2015;128(12):1325–34.e2. doi:10.1016/j.amjmed.2015.05.041.

    Article  PubMed  Google Scholar 

  61. Kiani AN, Magder LS, Post WS, et al. Coronary calcification in SLE: comparison with the Multi-Ethnic Study of Atherosclerosis. Rheumatology (Oxford). 2015;54(11):1976–81. doi:10.1093/rheumatology/kev198.

    Article  Google Scholar 

  62. Al Rifai M, Silverman MG, Nasir K, et al. The association of nonalcoholic fatty liver disease, obesity, and metabolic syndrome, with systemic inflammation and subclinical atherosclerosis: the Multi-Ethnic Study of Atherosclerosis (MESA). Atherosclerosis. 2015;239(2):629–33. doi:10.1016/j.atherosclerosis.2015.02.011.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  63. Miedema MD, Petrone A, Shikany JM, et al. Association of fruit and vegetable consumption during early adulthood with the prevalence of coronary artery calcium after 20 years of follow-up: the Coronary Artery Risk Development in Young Adults (CARDIA) study. Circulation. 2015;132(21):1990–8. doi:10.1161/CIRCULATIONAHA.114.012562.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  64. Miller PE, Zhao D, Frazier-Wood AC, et al. Associations between coffee, tea, and caffeine intake with coronary artery calcification and cardiovascular events. Am J Med. 2016. doi:10.1016/j.amjmed.2016.08.038.

    Google Scholar 

  65. Kim LK, Yoon JW, Lee DH, et al. Impact of metabolic syndrome on the progression of coronary calcium and of coronary artery disease assessed by repeated cardiac computed tomography scans. Cardiovasc Diabetol. 2016;15:92. doi:10.1186/s12933-016-0404-7.

    Article  PubMed  PubMed Central  Google Scholar 

  66. Basaria S, Harman SM, Travison TG, et al. Effects of testosterone administration for 3 years on subclinical atherosclerosis progression in older men with low or low-normal testosterone levels: a randomized clinical trial. JAMA. 2015;314(6):570–81. doi:10.1001/jama.2015.8881.

    Article  CAS  PubMed  Google Scholar 

  67. Roy SK, Estrella MM, Darilay AT, et al. Glomerular filtration rate and proteinuria associations with coronary artery calcium among HIV-infected and HIV-uninfected men in the multicenter AIDS cohort study. Coron Artery Dis. 2016. doi:10.1097/MCA.0000000000000428.

    PubMed  Google Scholar 

  68. Kim JJ, Hwang BH, Choi IJ, et al. A prospective two-center study on the associations between microalbuminuria, coronary atherosclerosis and long-term clinical outcome in asymptomatic patients with type 2 diabetes mellitus: evaluation by coronary CT angiography. Int J Cardiovasc Imaging. 2015;31(1):193–203. doi:10.1007/s10554-014-0541-6.

    Article  PubMed  Google Scholar 

  69. Chaikriangkrai K, Valderrabano M, Bala SK, et al. Prevalence and Implications of subclinical coronary artery disease in patients with atrial fibrillation. Am J Cardiol. 2015;116(8):1219–23. doi:10.1016/j.amjcard.2015.07.041.

    Article  PubMed  Google Scholar 

  70. Uehara M, Funabashi N, Takaoka H, et al. The CHADS2 score is a useful predictor of coronary arteriosclerosis on 320 slice CT and may correlate with prognosis in subjects with atrial fibrillation. Int J Cardiol. 2015;179:84–9. doi:10.1016/j.ijcard.2014.10.151.

    Article  PubMed  Google Scholar 

  71. Maragiannis D, Schutt RC, Gramze NL, et al. Association of left ventricular diastolic dysfunction with subclinical coronary atherosclerotic disease burden using coronary artery calcium scoring. J Atheroscler Thromb. 2015;22(12):1278–86. doi:10.5551/jat.29454.

    Article  CAS  PubMed  Google Scholar 

  72. Feldman DI, Cainzos-Achirica M, Billups KL, et al. Subclinical vascular disease and subsequent erectile dysfunction: the Multiethnic Study of Atherosclerosis (MESA). Clin Cardiol. 2016;39(5):291–8. doi:10.1002/clc.22530.

    Article  PubMed  Google Scholar 

  73. Whitlock MC, Yeboah J, Burke GL, et al. Cancer and its association with the development of coronary artery calcification: an assessment from the Multi-Ethnic Study of Atherosclerosis. J Am Heart Assoc. 2015;4(11):pii.e002533. doi:10.1161/JAHA.115.002533.

    Article  Google Scholar 

  74. Bahrami H, Budoff M, Haberlen SA, et al. Inflammatory markers associated with subclinical coronary artery disease: the multicenter AIDS cohort study. J Am Heart Assoc. 2016;5(6):pii.e003371. doi:10.1161/JAHA.116.003371.

    Article  Google Scholar 

  75. Chow D, Young R, Valcour N, et al. HIV and coronary artery calcium score: comparison of the Hawaii aging with HIV cardiovascular study and Multi-Ethnic Study of Atherosclerosis (MESA) cohorts. HIV Clin Trials. 2015;16(4):130–8. doi:10.1179/1528433614Z.0000000016.

    Article  PubMed  PubMed Central  Google Scholar 

  76. Sinn DH, Kang D, Chang Y, et al. Non-alcoholic fatty liver disease and progression of coronary artery calcium score: a retrospective cohort study. Gut. 2016. doi:10.1136/gutjnl-2016-311854.

    PubMed  Google Scholar 

  77. Lee MK, Park HJ, Jeon WS, et al. Higher association of coronary artery calcification with non-alcoholic fatty liver disease than with abdominal obesity in middle-aged Korean men: the Kangbuk Samsung health study. Cardiovasc Diabetol. 2015;14:88. doi:10.1186/s12933-015-0253-9.

    Article  PubMed  PubMed Central  Google Scholar 

  78. Jacobs K, Brouha S, Bettencourt R, et al. Association of nonalcoholic fatty liver disease with visceral adiposity but not coronary artery calcification in the elderly. Clin Gastroenterol Hepatol. 2016;14(9):1337–1344.e3. doi:10.1016/j.cgh.2016.01.010.

    Article  PubMed  Google Scholar 

  79. Chun S, Choi Y, Chang Y, et al. Sugar-sweetened carbonated beverage consumption and coronary artery calcification in asymptomatic men and women. Am Heart J. 2016;177:17–24. doi:10.1016/j.ahj.2016.03.018.

    Article  CAS  PubMed  Google Scholar 

  80. Choi Y, Chang Y, Ryu S, et al. Relation of dietary glycemic index and glycemic load to coronary artery calcium in asymptomatic Korean adults. Am J Cardiol. 2015;116(4):520–6. doi:10.1016/j.amjcard.2015.05.005.

    Article  CAS  PubMed  Google Scholar 

  81. Kianoush S, Al Rifai M, Whelton SP, et al. Stratifying cardiovascular risk in diabetes: the role of diabetes-related clinical characteristics and imaging. J Diabetes Complicat. 2016;30(7):1408–15. doi:10.1016/j.jdiacomp.2016.04.021.

    Article  PubMed  Google Scholar 

  82. Moody WE, Lin EL, Stoodley M, et al. Prognostic utility of calcium scoring as an adjunct to stress myocardial perfusion scintigraphy in end-stage renal disease. Am J Cardiol. 2016;117(9):1387–96. doi:10.1016/j.amjcard.2016.02.003.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  83. Winther S, Svensson M, Jorgensen HS, et al. Diagnostic performance of coronary CT angiography and myocardial perfusion imaging in kidney transplantation candidates. JACC Cardiovasc Imaging. 2015;8(5):553–62. doi:10.1016/j.jcmg.2014.12.028.

    Article  PubMed  Google Scholar 

  84. Bellasi A, Ferramosca E, Ratti C, et al. The density of calcified plaques and the volume of calcium predict mortality in hemodialysis patients. Atherosclerosis. 2016;250:166–71. doi:10.1016/j.atherosclerosis.2016.03.034.

    Article  CAS  PubMed  Google Scholar 

  85. Chadashvili T, Litmanovich D, Hall F, Slanetz PJ. Do breast arterial calcifications on mammography predict elevated risk of coronary artery disease? Eur J Radiol. 2016;85(6):1121–4. doi:10.1016/j.ejrad.2016.03.006.

    Article  PubMed  Google Scholar 

  86. Newallo D, Meinel FG, Schoepf UJ, et al. Mammographic detection of breast arterial calcification as an independent predictor of coronary atherosclerotic disease in a single ethnic cohort of African American women. Atherosclerosis. 2015;242(1):218–21. doi:10.1016/j.atherosclerosis.2015.07.004.

    Article  CAS  PubMed  Google Scholar 

  87. Margolies L, Salvatore M, Hecht HS, et al. Digital mammography and screening for coronary artery disease. JACC Cardiovasc Imaging. 2016;9(4):350–60. doi:10.1016/j.jcmg.2015.10.022.

    Article  PubMed  Google Scholar 

  88. Metkus TS, Brown T, Budoff M, et al. HIV infection is associated with an increased prevalence of coronary noncalcified plaque among participants with a coronary artery calcium score of zero: Multicenter AIDS Cohort Study (MACS). HIV Med. 2015;16(1):635–9. doi:10.1111/hiv.12262.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  89. Gaisl T, Schlatzer C, Schwarz EI, et al. Coronary artery calcification, epicardial fat burden, and cardiovascular events in chronic obstructive pulmonary disease. PLoS One. 2015;10(5), e0126613. doi:10.1371/journal.pone.0126613.

    Article  PubMed  PubMed Central  Google Scholar 

  90. Takx RA, Vliegenthart R, Mohamed Hoesein FA, et al. Pulmonary function and CT biomarkers as risk factors for cardiovascular events in male lung cancer screening participants: the NELSON study. Eur Radiol. 2015;25(1):65–71. doi:10.1007/s00330-014-3384-6.

    Article  PubMed  Google Scholar 

  91. McEvoy JW, Martin SS, Blaha MJ, et al. The case for and against a coronary artery calcium trial. JACC Cardiovasc Imaging. 2016;9(8):994–1002. doi:10.1016/j.jcmg.2016.03.012.

    Article  PubMed  Google Scholar 

  92. Ladeiras-Lopes R, Bettencourt N, Ferreira N, et al. CT myocardial perfusion and coronary CT angiography: influence of coronary calcium on a stress-rest protocol. J Cardiovasc Comput Tomogr. 2016;10(3):215–20. doi:10.1016/j.jcct.2016.01.013.

    Article  PubMed  Google Scholar 

  93. Kim BJ, Cheong ES, Kang JG, et al. Relationship of epicardial fat thickness and nonalcoholic fatty liver disease to coronary artery calcification: from the CAESAR study. J Clin Lipidol. 2016;10(3):619–626.e1. doi:10.1016/j.jacl.2016.01.008.

    Article  PubMed  Google Scholar 

  94. Millard HR, Musani SK, Dibaba DT, et al. Dietary choline and betaine; associations with subclinical markers of cardiovascular disease risk and incidence of CVD, coronary heart disease and stroke: the Jackson Heart Study. Eur J Nutr. 2016. doi:10.1007/s00394-016-1296-8.

    PubMed  Google Scholar 

  95. Choi Y, Chang Y, Lee JE, et al. Egg consumption and coronary artery calcification in asymptomatic men and women. Atherosclerosis. 2015;241(2):305–12. doi:10.1016/j.atherosclerosis.2015.05.036.

    Article  CAS  PubMed  Google Scholar 

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Correspondence to Seth S. Martin.

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Vasanth Sathiyakumar and Roger S. Blumenthal declare that they have no conflict of interest.

Khurram Nasir declares personal fees from the Advisory Board for Quest Diagnostics and from Consultant for Regeneronon.

Seth S. Martin declares grant support from PJ Schafer Cardiovascular Research Fund, American Heart Association, Aetna Foundation, CASCADE FH, Google, Apple, and the David and June Trone Family Foundation. He also declares personal fees from Abbott Nutrition, Pressed Juicery, Quest Diagnostics, Sanofi/Regeneron, Amgen, and Pew Research Center. Dr. Martin is also listed as a co-inventor on a pending patent filed by Johns Hopkins University for the novel method of low-density lipoprotein cholesterol estimation.

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Sathiyakumar, V., Blumenthal, R.S., Nasir, K. et al. Addressing Knowledge Gaps in the 2013 ACC/AHA Guideline on the Assessment of Cardiovascular Risk: a Review of Recent Coronary Artery Calcium Literature. Curr Atheroscler Rep 19, 7 (2017). https://doi.org/10.1007/s11883-017-0643-4

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